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Improving End-to-End Training of Retrieval-Augmented Generation Models via Joint Stochastic Approximation
Hongyu Cao, Yuxuan Wu, Yucheng Cai +2
Retrieval-augmented generation (RAG) has become a widely recognized paradigm to combine parametric memory with non-parametric memories. An RAG model consists of two serial connecti…
Knowledge Augmented Finetuning Matters in both RAG and Agent Based Dialog Systems
Yucheng Cai, Yuxuan Wu, Yi Huang +2
Large language models (LLMs) have recently been applied to dialog systems. Despite making progress, LLMs are prone to errors in knowledge-intensive scenarios. Recently, approaches…
Efficient Machine Translation with a BiLSTM-Attention Approach
Yuxu Wu, Yiren Xing
With the rapid development of Natural Language Processing (NLP) technology, the accuracy and efficiency of machine translation have become hot topics of research. This paper propos…
CodeUnlearn: Amortized Zero-Shot Machine Unlearning in Language Models Using Discrete Concept
YuXuan Wu, Bonaventure F. P. Dossou, Dianbo Liu
Large Language Models (LLMs) offer extensive knowledge across various domains, but they may inadvertently memorize sensitive, unauthorized, or malicious data, such as personal info…